Methods and systems for reducing spillover by measuring a crest factor

ABSTRACT

Methods, apparatus, and articles of manufacture for reducing spillover in a media monitoring system are disclosed. An example method includes comparing a first crest factor stored in association with a media identifier to a second crest factor calculated by a first meter, the second crest factor corresponding to a ratio of a peak amplitude of an audio signal and a root mean square value of the audio signal. The example method also includes determining that spillover did not occur if a difference between the first crest factor and the second crest factor satisfies a threshold, and when the spillover did not occur, crediting a media exposure to media associated with the audio signal.

RELATED APPLICATIONS

This patent arises from a continuation of U.S. patent application Ser.No. 13/782,895, filed Mar. 1, 2013, granted as U.S. Pat. No. 9,021,516and which is incorporated by reference in its entirety herein.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to media monitoring and, moreparticularly, to methods and systems for reducing spillover by measuringa crest factor.

BACKGROUND

Audience measurement of media, such as television, music, movies, radio,Internet websites, streaming media, etc., is typically carried out bymonitoring media exposure of panelists that are statistically selectedto represent particular demographic groups. Using various statisticalmethods, the captured media exposure data is processed to determine thesize and demographic composition of the audience(s) for programs ofinterest. The audience size and demographic information is valuable toadvertisers, broadcasters and/or other entities. For example, audiencesize and demographic information is a factor in the placement ofadvertisements, as well as a factor in valuing commercial time slotsduring a particular program.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system including an example spillovermanager implemented in accordance with the teachings of this disclosureto manage spillover to reduce media monitoring inaccuracies in thesystem.

FIG. 2A illustrates an example implementation of an example meter ofFIG. 1.

FIG. 2B illustrates an example audio waveform analyzed by the examplemeter of FIG. 2A.

FIG. 3 illustrates an example implementation of the example spillovermanager of FIG. 1.

FIG. 4 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example spillovermanager of FIGS. 1 and/or 3.

FIG. 5 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example meter ofFIGS. 1 and/or 2.

FIG. 6 is another flow diagram representative of example machinereadable instructions that may be executed to implement the examplespillover manager of FIGS. 1 and/or 3.

FIG. 7 is a block diagram of an example processor platform that may beused to execute the instructions of FIGS. 4, 5, and/or 6 to implementthe example meter 106 of FIG. 2A, the example spillover manager of FIG.3, and/or, more generally, the example system of FIG. 1.

DETAILED DESCRIPTION

Audience measurement companies enlist persons to participate inmeasurement panels. Such persons (e.g., panelists) agree to allow theaudience measurement company to measure their exposure to media (e.g.,television programming, radio programming, Internet, advertising,signage, outdoor advertising, etc.). In order to credit media monitoringdata with panelist exposure, the audience measurement company monitorsmedia device(s) and/or panelist(s) using meters.

In some examples, meters (e.g., stationary meters) are placed withand/or near media presentation devices (e.g., televisions, stereos,speakers, computers, etc.) within a home or household. For example, ameter may be placed in a room with a television and another meter may beplaced in a different room with another television. In some examples,personal portable metering devices (PPMs), which are also known asportable metering devices or portable personal meters, are used tomonitor media exposure of panelists. A PPM is an electronic device thatis typically worn (e.g., clipped to a belt or other apparel) or carriedby a panelist. The term “meter” as used herein refers generally tostationary meters and/or portable meters.

In general, meters are configured to use a variety of techniques tomonitor media presentations at media presentation devices and/orexposure of panelists to media presentations. For example, one techniquefor monitoring media exposure involves detecting or collectinginformation (e.g., codes (e.g., watermarks), signatures, etc.) frommedia signals (e.g., audio and/or video signals) that are emitted orpresented by media presentation devices.

As media is presented, a meter may receive media signals (e.g., via amicrophone) associated with the media and may detect media (e.g., audioand/or video) information associated with the media to generate mediamonitoring data. In general, media monitoring data may include anyinformation that is representative of (or associated with) media and/orthat may be used to identify a particular media presentation (e.g., asong, a television program, a movie, a video game, an advertisement,etc.). For example, the media monitoring data may include signaturesthat are collected or generated by the meter based on the media, audiocodes that are broadcast simultaneously with (e.g., embedded in) themedia, etc. Each meter may receive different media signals based on themedia presented on the media presentation devices to which panelists areexposed.

Media monitoring systems may also include one or more people meters toidentify panelists in a monitored audience. Identifying the panelists inthe audience allows mapping of their demographics to the media.Panelists provide their demographic information when they agree to bemonitored by the audience measurement system. Any method of peoplemetering may be employed. For example, the people metering may be activein that it requires panelists to periodically self-identify by, forinstance, entering an identifier corresponding to their name, or it maybe passive in that electronics (e.g., video cameras) may be used toidentify and/or count persons in the audience. See U.S. Pat. No.7,609,853, which is hereby incorporated by reference herein in itsentirety for an example people metering solution.

A panelist home may present unique monitoring challenges to the meters.For example, a panelist home often includes multiple media presentationdevices, each configured to present media to specific viewing and/orlistening areas located within the home. Known meters that are locatedin one of the viewing and/or listening areas are typically configured todetect any media being presented in the viewing and/or listening areaand to credit the media as having been presented. Thus, known metersoperate on the premise that any media detected by the meter is mediathat was presented in that particular viewing and/or listening area.However, in some cases, a meter may detect media that is emitted by amedia presentation device that is not located within the viewing orlistening proximity of a panelist being monitored thereby causing thedetected media to be improperly credited to the panelist currentlyassociated with the monitored area (via, for example, a people meter).The ability of the meter to detect media being presented outside of theviewing and/or listening proximity of the panelist is referred to as“spillover” because the media being presented outside of the viewingand/or listening proximity of the panelist is “spilling over” into thearea occupied by the meter and may not actually fall within theattention of the panelist. Spillover may occur, for example, when atelevision in a particular room is powered off, but a meter associatedwith that television detects media being presented on a mediapresentation device in a different room. In such an example, the meterimproperly credits the media as being presented.

Another effect, referred to as “hijacking,” occurs when a meter detectsdifferent media being presented at multiple media presentation devicesat the same time. For example, a meter in a kitchen may detect aparticular media program being presented on a media presentation devicein the kitchen, but the meter may also detect a different media programthat is being presented on a different media presentation device in aliving room. In such an example, the media presented by the mediapresentation device in the living room may, in some cases, have signalsthat overpower or “hijack” the signals associated with the media beingpresented by the media presentation device in the kitchen. As a result,the meter in the kitchen may inaccurately credit the media beingpresented in the living room and fail to credit the media beingpresented in the kitchen. In some examples, other difficulties such asvarying volume levels, varying audio/video content type (e.g., sparse,medium, rich, etc.), varying household transmission characteristics dueto open/closed doors, movement and/or placement of furniture, acousticcharacteristics of room layouts, wall construction, floor coverings,ceiling heights, etc. may exacerbate these issues and, thus, lead toinaccurate media presentation detection by meters.

Example methods and systems disclosed herein may be used to manage audiospillover and/or other sources of media monitoring inaccuracies in thecourse of presentations of media to more accurately assess the exposureof panelists to that media. Example methods and systems may be used toprevent audio spillover from adversely affecting results of mediamonitoring. Some example methods and systems analyze media monitoringdata to determine if audio spillover has occurred. In some suchexamples, if audio spillover has not occurred, the media is credited asactual media exposure (e.g., a panelist has been exposed to the media).If audio spillover has occurred, the media is not credited as an actualmedia exposure.

Example methods and systems disclosed herein detect signal spillover byanalyzing crest factors associated with media presentations (e.g., crestfactors of audio signal waveforms representative of mediapresentations). As used herein, a crest factor is defined to be ameasurement of a waveform which is calculated from a peak amplitude ofthe waveform divided by a root mean square (RMS) value of the waveform.Particular media presentations (e.g., particular media content and/oradvertisements) have particular crest factors associated with them(e.g., a particular crest factor may be expected from a particular mediapresentation). A crest factor expected from a particular mediapresentation is referred to herein as an expected crest factor. In someexamples, a meter monitoring a media presentation from a proximate mediapresentation device may analyze a waveform of the media presentation andcalculate a received crest factor. In some examples, the received crestfactor is compared to the expected crest factor to determine ifspillover has occurred. For example, the received crest factor may bedifferent from the expected crest factor (e.g., reduced) when the audiohas traveled a larger distance than expected, the audio has beentransmitted through different rooms (e.g., the signal has bounced off ofwalls, traveled through a wall, a ceiling, or a floor, etc.), etc. Ifthe received crest factor is similar to the expected crest factor (e.g.,within a threshold amount), it is determined that spillover has notoccurred. If the received crest factor is not similar to the expectedcrest factor (e.g., within a threshold amount), it is determined thatspillover has occurred. In some examples, when it is determined thatspillover has occurred, the media presentation is not credited as anactual media exposure.

An example method includes identifying media associated with mediamonitoring data. The media monitoring data is received from a firstmeter associated with a first media presentation device. The examplemethod includes identifying an expected crest factor associated with themedia. The example method includes comparing the expected crest factorto a received crest factor to determine if spillover occurred. Thereceived crest factor is received from the first meter. The examplemethod includes crediting the media as a media exposure if spillover didnot occur.

An example spillover manager disclosed herein includes a crest factorcomparator to identify media associated with media monitoring data. Themedia monitoring data is received from a meter associated with a mediapresentation device. The example crest factor comparator is to identifyan expected crest factor associated with the media. The example crestfactor comparator is to compare the expected crest factor to a receivedcrest factor to determine if spillover occurred. The received crestfactor is received from the meter. The example spillover managerincludes a media creditor to credit the media with an exposure ifspillover did not occur and to not credit the media with an exposure ifspillover did occur.

An example tangible computer readable storage medium disclosed hereincomprises instructions that, when executed, cause a computing device toidentify media associated with media monitoring data. The mediamonitoring data is received from a first meter associated with a firstmedia presentation device. The example instructions cause the computingdevice to identify an expected crest factor associated with the media.The example instructions cause the computing device to compare theexpected crest factor to a received crest factor to determine ifspillover occurred. The received crest factor is received from the firstmeter. The example instructions cause the computing device to credit themedia as a media exposure if spillover did not occur.

FIG. 1 illustrates an example system 100 including an example spillovermanager 102 within a home processing system 104 implemented inaccordance with the teachings of this disclosure to manage spillover toreduce (e.g., prevent) media monitoring inaccuracies in the system 100.In the illustrated example, a first meter 106 monitors media presentedon a first media presentation device 108 in a first room 110 and asecond meter 112 monitors media presented on a second media presentationdevice 114 in a second room 116. Either or both of the first and secondmedia presentation devices 108, 114 may be, for example, a television, aradio, a computer, a stereo system, a DVD player, a game console, etc.Media may include, for example, television programming, radioprogramming, movies, songs, advertisements, Internet information such aswebsites and/or streaming media, and/or any other video information,audio information, still image information, and/or computer informationto which a panelist (e.g., an example panelist 118) may be exposed.While two rooms 110, 116, two media presentation devices 108, 114, andtwo meters 106, 112 are shown in the example of FIG. 1, any number ofrooms, media presentation devices, and/or meters in any configurationmay be implemented in the example system 100.

In the illustrated example, to monitor media presented on the first andsecond media presentation devices 108, 114, the first and second meters106, 112 process media signals (or portions thereof such as audioportions of the media signals) respectively output by the first andsecond media presentation devices 108, 114 to extract codes and/ormetadata, and/or to generate signatures for use in identifying the mediaand/or a station (e.g., a broadcaster) originating the media.

Identification codes, such as watermarks, ancillary codes, etc. may beembedded within or otherwise transmitted with media signals.Identification codes are data that are inserted into media (e.g., audio)to uniquely identify broadcasters and/or media (e.g., content oradvertisements), and/or are carried with the media for another purposesuch as tuning (e.g., packet identifier headers (“PIDs”) used fordigital broadcasting). Codes are typically extracted using a decodingoperation.

Signatures are a representation of one or more characteristic(s) of themedia signal (e.g., a characteristic of the frequency spectrum of thesignal). Signatures can be thought of as fingerprints. They aretypically not dependent upon insertion of identification codes in themedia, but instead preferably reflect an inherent characteristic of themedia and/or the media signal. Systems to utilize codes and/orsignatures for audience measurement are long known. See, for example,Thomas, U.S. Pat. No. 5,481,294, which is hereby incorporated byreference in its entirety. Codes, metadata, signatures, etc. collectedand/or generated by the meters 106 and/or 112 for use in identifyingmedia and/or a station transmitting media may be referred to generallyas media monitoring data.

In the illustrated example, media monitoring data collected by the firstmeter 106 and/or the second meter 112 is transferred to the homeprocessing system 104 for further processing. The first and secondmeters 106, 112 may be communicatively coupled with the home processingsystem 104 via wireless and/or hardwired communications and mayperiodically and/or aperiodically communicate collected monitoringinformation to the home processing system 104.

In the illustrated example, the home processing system 104 iscommunicatively coupled to a remotely located central data collectionfacility 120 via a network 122. The example home processing system 104of FIG. 1 transfers collected media monitoring data to the centralfacility 120 for further processing. The central facility 120 of theillustrated example collects and/or stores, for example, mediamonitoring data and/or demographic information that is collected bymultiple media monitoring devices such as, for example, the meters 106,112, located at multiple panelist locations. The central facility 120may be, for example, a facility associated with The Nielsen Company(US), LLC or any affiliate of The Nielsen Company (US), LLC. The centralfacility 120 of the illustrated example includes a server 124 and adatabase 126 that may be implemented using any suitable processor,memory and/or data storage apparatus such as that shown in FIG. 7. Insome examples, the home processing system 104 is located in the centralfacility 120.

The network 122 of the illustrated example is used to communicateinformation and/or data between the example home processing system 104and the central facility 120. The network 122 may be implemented usingany type of public and/or private network such as, but not limited to,the Internet, a telephone network, a local area network (“LAN”), a cablenetwork, and/or a wireless network. To enable communication via thenetwork 122, the home processing system 104 of the illustrated exampleincludes a communication interface that enables connection to anEthernet, a digital subscriber line (“DSL”), a telephone line, a coaxialcable, and/or any wireless connection, etc.

Some methods for measuring media exposure or presentation track or logmedia presentations to which a panelist is exposed and award a mediaexposure credit to a media presentation when the panelist is in thevicinity of that media presentation. However, some such methods mayproduce inconsistent or inaccurate monitoring results due to spilloverthat occurs. For example, within the system 100, spillover may occurwhen the first media presentation device 108 is powered off (e.g., isnot presenting media), but the first meter 106 associated with the firstmedia presentation device 108 detects media being presented by thesecond media presentation device 114. In such an example, the firstmeter 106 will incorrectly credit the media presented at the secondmedia presentation device 114 as being presented to the panelist 118.Recording media data that has spilled over from another space (e.g., theroom 116) may result in an inaccurate representation of the mediapresented to the panelist 118. In some such examples, the panelist maynot even know or be aware of the media, but the electronics of the meter106 may still be sensitive enough to detect a code in the media.

The spillover manager 102 of the illustrated example is used to managespillover to reduce (e.g., prevent) media monitoring inaccuracies in thesystem 100. The example spillover manager 102 of FIG. 1 receives mediamonitoring data from the first example meter 106 and/or the secondexample meter 112 and analyzes the media monitoring data to determine ifspillover has occurred. In the illustrated example, if the examplespillover manager 102 detects spillover associated with the first meter106 and/or the second meter 112, the media identified in the mediamonitoring data is not credited as actual media exposure for themeter/monitored media presentation device that experienced the spilloverand the media monitoring data associated with the uncredited media isdiscarded and/or marked as invalid. In the illustrated example, if theexample spillover manager 102 does not detect spillover associated withthe first meter 106 and/or the second meter 112, the media identified inthe media monitoring data is credited as actual media exposure(s). Inthe illustrated example, the spillover manager 102 sends mediamonitoring data associated with credited media to the example centralfacility 120. In some examples, the spillover manager 102 labelsportion(s) of the media monitoring data as either associated withcredited or uncredited media and sends the identified media monitoringdata to the example central facility 120.

In the illustrated example, the spillover manager 102 detects spilloverby analyzing crest factors associated with media presentations (e.g.,crest factors of audio signal waveforms representative of mediapresentations). Particular media presentations (e.g., particular mediacontent and/or advertisements) have particular crest factors associatedwith them (e.g., a particular crest factor may be expected from aparticular media presentation). A crest factor expected from aparticular media presentation may be referred to as an expected crestfactor. The spillover manager 102 stores and/or accesses (e.g., from thecentral facility 120) expected crest factors for use in spilloverdetection.

In the illustrated example, the first and second meters 106, 112 receivemedia signals (e.g., audio) associated with media presentations (e.g.,via microphones). In the illustrated example, in addition to collectingmedia monitoring data from the received media signals, the example firstand second meters 106, 112 analyze audio waveforms of the media signalsand calculate crest factors of the audio waveforms. The example firstand second meters 106, 112 of the illustrated example calculate crestfactors of the audio waveforms by dividing peak amplitudes of thewaveforms by root mean square (RMS) values of the waveforms. The crestfactors calculated by the example first and second meters 106, 112 arereferred to as received crest factors because they represent the crestfactors of the audio waveforms after they have been presented on thefirst and second media presentation devices 108, 114 and received at thefirst and second meters 106, 112. The first and second meters 106, 112of the illustrated example timestamp the media monitoring data and thereceived crest factors and send the timestamped media monitoring dataand received crest factors to the example spillover manager 102 foranalysis.

The spillover manager 102 of the illustrated example uses the mediamonitoring data to identify the media presented at the first and/orsecond media presentation device 108, 114. Once the media is identified,the spillover manager 102 of the illustrated example finds the expectedcrest factor for that media. To determine if spillover occurred, thespillover manager 102 of the illustrated example compares the expectedcrest factor for the identified media to the received crest factorprovided by the example first and/or second meter 106, 112. If thereceived crest factor is similar to the expected crest factor (e.g.,within a threshold amount), the example spillover manager 102 determinesthat spillover did not occur. Thus, the persons (e.g., the panelist 118)identified as present by a first people meter 128 associated with thefirst meter 106/first media presentation device 108 or a second peoplemeter 130 associated with the second meter 112/second media presentationdevice 114 are credited as having been exposed to the media. If thereceived crest factor is not similar to the expected crest factor (e.g.,within a threshold amount), the example spillover manager 102 determinesthat spillover occurred. Thus, the persons (e.g., the user 118)identified as present by the first people meter 128 or the second people130 are not credited as having been exposed to the media. In someexamples, when the example spillover manager 102 of FIG. 1 determinesthat spillover has occurred, the media is not credited as actual mediaexposure at the corresponding media presentation device (e.g., mediapresentation devices 108, 114).

For example, the first example meter 106 receives a media signal andcalculates a received crest factor for the received media signal, inaddition to collecting media monitoring data for the received mediasignal. In such an example, the first meter 106 sends the received crestfactor and the media monitoring data to the example spillover manager102. The example spillover manager 102 identifies the media (e.g.,content or advertisement) from the media monitoring data and accesses(e.g., looks up in a local database or cache, retrieves from a remotedatabase such as a database at the central facility 120) an expectedcrest factor associated with that media. If the received crest factor issimilar to the expected crest factor, the example spillover manager 102assumes the media was presented on the first example media presentationdevice 108 corresponding to the first meter 106 (i.e., the meter thatprovided the media monitoring data under analysis) and credits the mediaas an actual media exposure at the corresponding media presentationdevice. Thus, the persons identified as present by the first peoplemeter 128 (e.g., the panelist 118) are credited as having been exposedto the media. If the received crest factor is not similar to theexpected crest factor, the example spillover manager 102 assumes themedia was not presented on the example media presentation device 108(e.g., the media was presented on the media presentation device 114 andthe media signal spilled over to the example meter 106), and does notcredit the media as an actual media exposure (e.g., does not credit themedia with exposure to the panelist 118).

While the spillover manager 102 of the illustrated example is shownwithin the example home processing system 104, the spillover manager 102may be implemented at the first meter 106, the second meter 112, and/orat the central facility 120.

FIG. 2A is a block diagram of an example implementation of the first andsecond meters 106, 112 of FIG. 1. The meter 106, 112 of the illustratedexample receives media signals (e.g., audio signals) from one or moremedia presentation devices (e.g., the media presentation device 108and/or 114 of FIG. 1). In the illustrated example, the meter 106, 112 isused to collect media monitoring data (e.g., to extract and/or analyzecodes and/or signatures from media signals output by a correspondingmedia presentation device 108, 114) and is used to calculate crestfactors of the media signals. The meter 106, 112 of the illustratedexample is used to collect, aggregate, locally process, and/or transfermedia monitoring data and/or crest factors to the spillover manager 102of FIG. 1. The meter 106, 112 of the illustrated example includes anexample input 202, an example code collector 204, an example signaturegenerator 206, example control logic 208, an example timestamper 210, anexample database 212, an example transmitter 214, and an example crestfactor calculator 216.

In the illustrated example, the input 202 is a microphone exposed toambient sound and serves to collect audio signals output by mediapresentation devices (e.g., the media presentation device 108). Tocollect media monitoring data associated with the audio signals, theinput 202 of the illustrated example passes a received audio signal tothe code collector 204 and/or the signature generator 206. The codecollector 204 of the illustrated example extracts codes and/or thesignature generator 206 generates signatures from the signal to identifybroadcasters, channels, stations, and/or programs. The control logic 208of the illustrated example is used to control the code collector 204and/or the signature generator 206 to cause collection of a code, asignature, or both a code and a signature. The identified codes and/orsignatures (e.g., the media monitoring data) are timestamped at theexample timestamper 210, are stored in the example database 212, and aretransmitted by the example transmitter 214 to the spillover manager 102at the home processing system 104. Although the example of FIG. 2Acollects codes and/or signatures from audio signals, codes or signaturescan additionally or alternatively be collected from other portion(s) ofthe signal (e.g., from the video portion).

The input 202 of the illustrated example also passes the received audiosignal to the example crest factor calculator 216. The crest factorcalculator 216 of the illustrated example calculates a crest factor forthe received audio signal by dividing a peak amplitude of the signal byan RMS value of the signal. An example equation to calculate a crestfactor is illustrated below.

$C = \frac{{x}_{peak}}{x_{rms}}$

FIG. 2B illustrates an example audio waveform 201 of an audio signalanalyzed by the example crest factor calculator 216 of FIG. 2A. Tocalculate a crest factor of the example audio waveform 201, the examplecrest factor calculator 216 divides a peak amplitude value 203 of theexample audio waveform 201 by an RMS value 205 of the example audiowaveform 201.

Returning to the description of FIG. 2A, the crest factor calculated bythe example crest factor calculator 216 is referred to as the receivedcrest factor. The received crest factor is timestamped at the exampletimestamper 210, stored at the example database 212, and transmitted bythe example transmitter 214 to the example spillover manager 102 withthe media monitoring data.

While an example manner of implementing the meter 106, 112 of FIG. 1 isillustrated in FIG. 2A, one or more of the elements, processes and/ordevices illustrated in FIG. 2A may be combined, divided, re-arranged,omitted, eliminated and/or implemented in any other way. Further, theexample input 202, the example code collector 204, the example signaturecollector 206, the example control logic 208, the example timestamper210, the example database 212, the example transmitter 214, the examplecrest factor calculator 216, and/or, more generally, the example meter106, 112 of FIG. 1 may be implemented by hardware, software, firmwareand/or any combination of hardware, software and/or firmware. Thus, forexample, any of the example input 202, the example code collector 204,the example signature collector 206, the example control logic 208, theexample timestamper 210, the example database 212, the exampletransmitter 214, the example crest factor calculator 216, and/or, moregenerally, the example meter 106, 112 could be implemented by one ormore circuit(s), programmable processor(s), application specificintegrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s))and/or field programmable logic device(s) (FPLD(s)), etc. When readingany of the apparatus or system claims of this patent to cover a purelysoftware and/or firmware implementation, at least one of the exampleinput 202, the example code collector 204, the example signaturecollector 206, the example control logic 208, the example timestamper210, the example database 212, the example transmitter 214, the examplecrest factor calculator 216, and/or the example meter 106, 112 arehereby expressly defined to include a tangible computer readable storagedevice or storage disc such as a memory, DVD, CD, Blu-ray, etc. storingthe software and/or firmware. Further still, the example meter 106, 112of FIG. 1 may include one or more elements, processes and/or devices inaddition to, or instead of, those illustrated in FIG. 2A, and/or mayinclude more than one of any or all of the illustrated elements,processes and devices.

FIG. 3 is a block diagram of an example implementation of the spillovermanager 102 of FIG. 1. The spillover manager 102 of the illustratedexample receives media monitoring data and received crest factors fromone or more meter(s) (e.g., the meters 106, 112 of FIG. 1). In theillustrated example, the spillover manager 102 uses the media monitoringdata and received crest factors to determine whether spillover occurred(e.g., in the example system 100 of FIG. 1) and whether identified mediaprograms are to be credited with actual exposure to a panelist. Thespillover manager 102 of the illustrated example is used to transfercredited media monitoring data (e.g., media monitoring data associatedwith credited media programs) to the central facility 120 of FIG. 1. Thespillover manager 102 of the illustrated example includes an examplecrest factor comparator 302, an example crest factor database 304, anexample media creditor 306, and an example transmitter 308.

The crest factor comparator 302 of the illustrated example receivesmedia monitoring data and received crest factors from the meter(s)(e.g., the first and second meters 106, 112 of FIG. 1). The crest factorcomparator 302 of the illustrated example uses the example crest factordatabase 304 to identify media (e.g., media that was presented by themedia presentation device 108 or 114) based on the media monitoring dataand to identify an expected crest factor associated with the identifiedmedia. Particular media programs are identified in the example crestfactor database 304 using the media monitoring data (e.g., using codesand/or signatures associated with the media). The crest factor database304 of the illustrated example stores media (e.g., different mediaprograms) along with expected crest factors associated with the media.For example, for each particular media program, the example crest factordatabase 304 stores an expected crest factor. Expected crest factors maybe calculated and/or determined at, for example, a central facility(e.g., the central facility 120 of FIG. 1) prior to implementation ofthe example spillover manager 102 in the example system 100 of FIG. 1and/or the spillover manager 102 may be implemented at the centralfacility 120 to process data collected from various meters.

Once the crest factor comparator 302 obtains the expected crest factorassociated with the media, the crest factor comparator 302 of theillustrated example compares the expected crest factor to the receivedcrest factor (e.g., the received crest factor received from themeter(s)). If the received crest factor is similar to the expected crestfactor (e.g., if a difference between the received crest factor and theexpected crest factor is within a threshold amount), the crest factorcomparator 302 of the illustrated example determines spillover did notoccur and instructs the example media creditor 306 to credit the mediaas an actual media exposure. If the received crest factor is not similarto the expected crest factor (e.g., if the difference between thereceived crest factor and the expected crest factor is not within thethreshold amount), the crest factor comparator 302 of the illustratedexample determines that spillover did occur and instructs the examplemedia creditor 306 to not credit the media as an actual media exposure.An example threshold amount is 6 decibels (dB).

The media creditor 306 of the illustrated example credits/does notcredit media as actual media exposure based on the output of the examplecrest factor comparator 302. If the example crest factor comparator 302determines that spillover did not occur, the media creditor 306 of theillustrated example marks the media monitoring data associated with themedia as credited. If the example crest factor comparator 302 determinesthat spillover did occur, the media creditor 306 of the illustratedexample discards the media monitoring data associated with the media. Insome examples, rather than discarding the media monitoring dataassociated with the media that is not credited, the example mediacreditor 306 marks the media monitoring data associated with the mediaas uncredited.

The transmitter 308 of the illustrated example transmits the creditedmedia monitoring data to a central facility (e.g., the central facility120 of FIG. 1) for further processing. In some examples, where theexample media creditor 306 does not discard the uncredited mediamonitoring data, the example transmitter 308 transmits the creditedmedia monitoring data and the uncredited media monitoring data to thecentral facility 120 for further processing.

While an example manner of implementing the spillover manager 102 ofFIG. 1 is illustrated in FIG. 3, one or more of the elements, processesand/or devices illustrated in FIG. 3 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example crest factor comparator 302, the example crestfactor database 304, the example media creditor 306, the exampletransmitter 308, and/or, more generally, the example spillover manager102 of FIG. 1 may be implemented by hardware, software, firmware and/orany combination of hardware, software and/or firmware. Thus, forexample, any of the example crest factor comparator 302, the examplecrest factor database 304, the example media creditor 306, the exampletransmitter 308, and/or, more generally, the example spillover manager102 could be implemented by one or more circuit(s), programmableprocessor(s), application specific integrated circuit(s) (ASIC(s)),programmable logic device(s) (PLD(s)) and/or field programmable logicdevice(s) (FPLD(s)), etc. When reading any of the apparatus or systemclaims of this patent to cover a purely software and/or firmwareimplementation, at least one of the example crest factor comparator 302,the example crest factor database 304, the example media creditor 306,the example transmitter 308, and/or the example spillover manager 102are hereby expressly defined to include a tangible computer readablestorage device or storage disc such as a memory, DVD, CD, Blu-ray, etc.storing the software and/or firmware. Further still, the examplespillover manager 102 of FIG. 1 may include one or more elements,processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 3, and/or may include more than one of any or all ofthe illustrated elements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the meter 106 of FIGS. 1 and 2 and the spillover manager102 of FIGS. 1 and 3 are shown in FIGS. 4, 5, and 6. In this example,the machine readable instructions comprise a program for execution by aprocessor such as the processor 712 shown in the example processorplatform 700 discussed below in connection with FIG. 7. The program maybe embodied in software stored on a tangible computer readable storagemedium such as a CD-ROM, a floppy disk, a hard drive, a digitalversatile disk (DVD), a Blu-ray disk, or a memory associated with theprocessor 712, but the entire program and/or parts thereof couldalternatively be executed by a device other than the processor 712and/or embodied in firmware or dedicated hardware. Further, although theexample program is described with reference to the flowchartsillustrated in FIGS. 4, 5, and 6, many other methods of implementing theexample meter 106 and the example spillover manager 102 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined.

As mentioned above, the example processes of FIGS. 4, 5, and 6 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals. As used herein, “tangible computerreadable storage medium” and “tangible machine readable storage medium”are used interchangeably. Additionally or alternatively, the exampleprocesses of FIGS. 4, 5, and 6 may be implemented using codedinstructions (e.g., computer and/or machine readable instructions)stored on a non-transitory computer and/or machine readable medium suchas a hard disk drive, a flash memory, a read-only memory, a compactdisk, a digital versatile disk, a cache, a random-access memory and/orany other storage device or storage disk in which information is storedfor any duration (e.g., for extended time periods, permanently, forbrief instances, for temporarily buffering, and/or for caching of theinformation). As used herein, the term non-transitory computer readablemedium is expressly defined to include any type of computer readabledevice or disc and to exclude propagating signals. As used herein, whenthe phrase “at least” is used as the transition term in a preamble of aclaim, it is open-ended in the same manner as the term “comprising” isopen ended.

FIG. 4 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example spillovermanager 102 of FIG. 1 to manage audio spillover in the example system100 of FIG. 1. The spillover manager 102 of the illustrated example isused to manage spillover to reduce (e.g., prevent) media monitoringinaccuracies in the system 100.

The example spillover manager 102 determines if media monitoring datahas been received (block 402). The example spillover manager 102 is toreceive media monitoring data from one or more meter(s) (e.g., the firstand/or second meters 106, 112 of FIG. 1). The media monitoring data isrepresentative of media that has been presented on one or more mediapresentation device(s) (e.g., the first and/or second media presentationdevices 108, 114 of FIG. 1). Control remains at block 402 until mediamonitoring data is received by the example spillover manager 102).

The example spillover manager 102 of the illustrated example analyzesthe media monitoring data to determine if spillover has occurred (block404). An example method to determine if spillover has occurred isdescribed below with reference to FIG. 6. If the example spillovermanager 102 detects spillover associated with the first and/or secondmeters 106, 112 based on the media monitoring data, the media identifiedin the media monitoring data is not credited as an actual media exposure(block 406) and the media monitoring data associated with the uncreditedmedia is discarded (block 408). Control then returns to block 402. Insome examples, rather than discarding the uncredited media monitoringdata, the example spillover manager 102 identifies the media monitoringdata as uncredited media and exports the uncredited media monitoringdata to a central facility (e.g., the example central facility 120).

If the example spillover manager 102 of the illustrated example does notdetect spillover associated with the first and/or the second meter 106,112, the media identified in the media monitoring data is credited as anactual media exposure (block 410). The example spillover manager 102 ofthe illustrated example exports media monitoring data associated withcredited media to the example central facility 120 (block 412). Controlthen returns to block 402 when the instructions are complete.

FIG. 5 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example meter 106,112 of FIG. 1 to collect media monitoring data and to calculate crestfactors. In the illustrated example, to collect media monitoring data,the meter 106, 112 extracts and/or analyzes codes and/or signatures fromdata and/or signals received from one or more media presentation devices(e.g., the first and/or the second media presentation devices 108, 114of FIG. 1).

Initially, the example input 202 obtains a signal (e.g., an audiosignal) from the one or more media presentation devices (e.g., the firstand/or the second media presentation devices 108, 114) (block 502). Theexample control logic 208 determines whether to collect a code orgenerate a signature from the signal obtained at the input 202 (block504). In the illustrated example, either a code is collected or asignature is generated from the signal. In other examples, both a codeand a signature are collected and/or generated.

If a code is to be collected, the example code collector 204 collects acode from the signal obtained at the input 202 (block 506). The examplecode collector 204 passes the collected code(s) to the timestamper 210.If a signature is to be generated, the signature generator 206 generatesa signature from the signal obtained at the input 202 (block 508). Theexample signature generator 206 passes the generated signature(s) to thetimestamper 210.

The example crest factor calculator 216 calculates a crest factor of thesignal obtained at the input 202 (block 510). The example crest factorcalculator 216 passes the received crest factor to the exampletimestamper 210. The example timestamper 210 timestamps the collectedcodes and/or generated signatures and the received crest factor (block512). The example timestamper 210 passes the collected codes and/orgenerated signatures and the received crest factor to the exampledatabase 212. The example database 212 stores the collected codes and/orgenerated signatures and the received crest factor (block 514). Theexample transmitter 214 periodically and/or aperiodically transmits thecollected codes and/or generated signatures and the received crestfactor to the spillover manager 102 of FIG. 1. Control then returns toblock 502 when the instructions are completed. In some examples, themeter 106, 112 may collect and timestamp the data, and periodically oraperiodically export the timestamped data for analysis by the spillovermanager 102 (which may be located at the panelist site or at the centralfacility). In such examples, blocks 504-510 and 514 are not performed inthe meter 106, 112, and blocks 512 and 516 are modified to operate onthe received signal (as opposed to on codes, signatures, and/or crestfactors).

FIG. 6 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example spillovermanager 102 of FIG. 3 to manage audio spillover in the example system100 of FIG. 1 using crest factors. The spillover manager 102 of theillustrated example is used to manage spillover to reduce mediamonitoring inaccuracies in the system 100.

The example spillover manager 102 receives media monitoring data andreceived crest factors from one or more meter(s) (e.g., the first and/orsecond meters 106, 112 of FIG. 1) (block 602). The example spillovermanager 102 uses the media monitoring data and received crest factors todetermine whether spillover occurred (e.g., in the example system 100 ofFIG. 1) and whether media programs are to be credited as actual mediaexposure.

The example crest factor comparator 302 uses the example crest factordatabase 304 to identify media (e.g., media that was presented at thefirst and/or the second media presentation device 108, 114) associatedwith the media monitoring data (block 604) and to identify an expectedcrest factor associated with the identified media (block 606).Particular media programs are identified in the example crest factordatabase 304 using the media monitoring data (e.g., using codes and/orsignatures associated with the media). The example crest factor database304 stores media (e.g., different media programs) along with expectedcrest factors associated with the media.

The example crest factor comparator 302 compares a difference betweenthe expected crest factor and the received crest factor (e.g., thereceived crest factor received from the first and/or the second meter106, 112) to a threshold (block 608). If the difference between thereceived crest factor and the expected crest factor is not within thethreshold amount (e.g., is greater than the threshold), the examplecrest factor comparator 302 determines that spillover did occur andinstructs the example media creditor 306 not to credit the media as anactual media exposure (block 610). If the example crest factorcomparator 302 determines that spillover did occur, the example mediacreditor 306 discards the media monitoring data associated with themedia (block 612). Control then returns to block 602. In some examples,rather than discarding the media monitoring data associated with themedia that is not credited, the example media creditor 306 marks themedia monitoring data associated with the media as uncredited.

If the difference between the received crest factor and the expectedcrest factor is within a threshold amount (e.g., less than thethreshold) (block 608), the example crest factor comparator 302determines spillover did not occur and the example media creditor 306credits the media as an actual media exposure (block 614). Inparticular, the example media creditor 306 marks the media monitoringdata associated with the media as credited (block 614). The exampletransmitter 308 transmits the credited media monitoring data to acentral facility (e.g., the central facility 120 of FIG. 1) for furtherprocessing (block 616). In some examples, where the example mediacreditor 306 does not discard the uncredited media monitoring data, theexample transmitter 308 transmits the credited media monitoring data andthe uncredited media monitoring data to the central facility 120 forfurther processing (block 616). Control then returns to block 602 whenthe instructions are complete.

FIG. 7 is a block diagram of an example processor platform 700 capableof executing the instructions of FIGS. 4, 5, and 6 to implement themeter 106 of FIGS. 1 and 2 and the spillover manager 102 of FIGS. 1 and3. The processor platform 700 can be, for example, a server, a personalcomputer, a mobile device (e.g., a cell phone, a smart phone, a tabletsuch as an iPad™), a personal digital assistant (PDA), an Internetappliance, a DVD player, a CD player, a digital video recorder, aBlu-ray player, a gaming console, a personal video recorder, a set topbox, or any other type of computing device.

The processor platform 700 of the illustrated example includes aprocessor 712. The processor 712 of the illustrated example is hardware.For example, the processor 712 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer.

The processor 712 of the illustrated example includes a local memory 713(e.g., a cache). The processor 712 of the illustrated example is incommunication with a main memory including a volatile memory 714 and anon-volatile memory 716 via a bus 718. The volatile memory 714 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 716 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 714, 716 is controlledby a memory controller.

The processor platform 700 of the illustrated example also includes aninterface circuit 720. The interface circuit 720 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 722 are connectedto the interface circuit 720. The input device(s) 722 permit a user toenter data and commands into the processor 712. The input device(s) canbe implemented by, for example, an audio sensor, a microphone, a camera(still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 724 are also connected to the interfacecircuit 720 of the illustrated example. The output devices 724 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a light emitting diode (LED), a printer and/or speakers).The interface circuit 720 of the illustrated example, thus, typicallyincludes a graphics driver card.

The interface circuit 720 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network726 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 700 of the illustrated example also includes oneor more mass storage devices 728 for storing software and/or data.Examples of such mass storage devices 728 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

The coded instructions 732 of FIGS. 4, 5, and 6 may be stored in themass storage device 728, in the volatile memory 714, in the non-volatilememory 716, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

Although certain example methods, apparatus and articles of manufacturehave been described herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A method to credit media, comprising: comparing,with a processor, a first crest factor stored in a memory in associationwith a media identifier to a second crest factor corresponding to aratio of a peak amplitude of an audio signal and a root mean squarevalue of the audio signal; determining, with the processor, thatspillover did not occur if a difference between the first crest factorand the second crest factor satisfies a threshold; and when thespillover did not occur, crediting, with the processor, a media exposureto media associated with the audio signal.
 2. The method as defined inclaim 1, further including associating, with a logic circuit, thecredited media with a person present in a room in which the audio signalis detected.
 3. The method as defined in claim 1, further includingdiscarding media monitoring data associated with the media identifierwhen spillover did occur.
 4. The method as defined in claim 1, whereinthe crediting of the media exposure to the media includes marking mediamonitoring data associated with the media identifier as credited.
 5. Themethod as defined in 1, wherein the threshold is about six decibels. 6.A spillover manager apparatus to credit media, comprising: a crestfactor comparator to: compare a first crest factor stored in a memory inassociation with a media identifier to a second crest factorcorresponding to a ratio of a peak amplitude of an audio signal and aroot mean square value of the audio signal, and determine that spilloverdid not occur if a difference between the first crest factor and thesecond crest factor satisfies a threshold; and a media creditor tocredit a media exposure to media associated with the audio signal whenthe spillover did not occur, the media creditor implemented using alogic circuit.
 7. The spillover manager as defined in claim 6, whereinthe media creditor is to associate the credited media with a personpresent in a room in which the audio signal is detected.
 8. Thespillover manager as defined in claim 6, wherein the media creditor isto discard media monitoring data associated with the media identifierwhen spillover did occur.
 9. The spillover manager as defined in claim6, wherein the media creditor is to credit the media exposure to themedia by marking media monitoring data associated with the mediaidentifier as credited.
 10. The spillover manager as defined in claim 6,wherein the threshold is about six decibels.
 11. A non-transitorycomputer readable storage medium comprising instructions that, whenexecuted by a processor, cause a computing device to at least: compare afirst crest factor stored in a memory in association with a mediaidentifier to a second crest factor corresponding to a ratio of a peakamplitude of an audio signal and a root mean square value of the audiosignal; determine that spillover did not occur if a difference betweenthe first crest factor and the second crest factor satisfies athreshold; and credit a media exposure to media associated with theaudio signal when the spillover did not occur.
 12. The computer readablestorage medium as defined in claim 11, wherein the instructions furthercause the computing device to associate the credited media with a personpresent in a room in which the audio signal is detected.
 13. Thecomputer readable storage medium as defined in claim 11, wherein theinstructions further cause the computing device to discard mediamonitoring data associated with the media identifier when spillover didoccur.
 14. The computer readable storage medium as defined in claim 11,wherein the instructions further cause the computing device to creditthe media with the media exposure by marking media monitoring dataassociated with the media identifier as credited.
 15. The computerreadable storage medium as defined in claim 11, wherein the threshold isabout six decibels.